Neural Network Representations
Alona explores the intriguing relationship between computer vision models and language representations, revealing how neural networks, despite lacking knowledge of language, learn semantic structures similar to those in word embeddings. The unexpected findings stemmed from a student's innovative approach, highlighting that as data progresses through the layers of a neural network, the representations increasingly mirror the semantic distances recognized in language models. This suggests a fascinating overlap in how concepts are understood across different modalities.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Using Brain Imaging to Improve Neural Networks with Alona Fyshe - #513
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